Business Intelligence Analyst Salary In India
Business Intelligence Analyst Salary In India – In today’s world, with every day passing by in seconds, we have a load of information in front of us. Be a part of social networks to find new trends, surf the web for the latest news, even your WhatsApp messages have in store for you some new funny jokes never heard.
However, this bombardment of information is a luxury only when we exploit it effectively to our advantage and our goals. In layman’s terms, one should know all the ins, whys and hows of this data or information in front of us for continuous growth.
Business Intelligence Analyst Salary In India
As more and more data is generated everywhere, more people and techniques will come to handle this data wisely. This brings in the scope of the concept of data analysis.
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You must think that what would be the salary of a data analyst in India? Or is the work really read in the data one procures?
This article will help you understand what data analysis is and everything there is to know about being a data analyst – skills required, job roles, data analyst salary for a new hire with experience, career path and the meaning of the role.
A complete process of obtaining useful data and analyzing it to make a more reliable decision-making process for a business or for the organization’s goals is called data analysis.
There are different ways to analyze data to make an informed decision for your business. Each type of analysis has a different purpose and methodology. It can be classified into four categories:
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Assuming in the scenario mentioned above, this analysis will determine why the employees wrote only 5 articles when the target was 7.
For example, based on the previous data you predict the time taken by a writer to write an article and based on this information give the company a predicted number of articles for a month.
Some people are curious, but some people want to not only ask questions but find answers to those questions. They procure a wide range of information, extract useful insights and find a solution to the problem.
A data analyst is a keen individual who gathers information (qualitative and quantitative) for the business industry and works towards making a strategic business decision. However, analyzing data is not just about number crunching, or observing facts. To arrive at an informed, best possible solution, the process needs to be productive and efficient.
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As the increase in data has increased significantly compared to previous years, the demand for a data analyst has improved. Therefore, a data analyst salary for a fresher could be a good start in India. It should be noted that the salary of a data analyst depends on many factors including experience, skills, location, and employer.
Experience plays a decisive role in finalizing the salary of a data analyst. A person’s experience in the field shows more knowledge, practical solutions, agile working and leadership skills to train others. Therefore, an analyst in the industry for more than three years will have a higher payment than the salary of a data analyst for a fresher.
A data analyst salary for a fresher might be different if located in Mumbai and data analyst salary in Bangalore. This is because the location is among one of the factors that affect the salary of the data analyst job.
Each city or state has a different cost of living and demand in the profession and accordingly the salary is decided.
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A data analyst to get a high-paying job with fewer years of experience should seek to master the different skills required for a data analyst. He/she has to look towards improving themselves beyond just a degree in data analysis.
Different companies and employers have different requirements in mind while hiring a data analyst. Based on the company’s position in the market, the job role and the skills required, the salary of a data analyst is also affected by the company.
It is rightly said, “Information is the oil of the 21st century, and analytics is the engine that releases the combustion.”
If you have good knowledge about the field of data analysis and suitable for the responsibilities to support it, then there are a wide range of areas you could work on:
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However, there are times when people overlap the roles of a data scientist and data engineer with a data analyst. Let’s take a closer look at the differences between the two in comparison with data analysts.
Data Scientists are experts who are skilled in programming, mathematics and statistics. They, and their influential learning in languages like Python, R, and Scala and SQL work on the business analysis in general.
Data scientists can do the work of a data analyst but for more complex problems based on diversified training. Mathematical models, heavy algorithms and data inference techniques are used to obtain information for future predictions. Unlike many data analysts, machine learning prioritizes past data.
The expertise of data engineers lies in the knowledge of software and database development. They do not work on analysis and instead have orders on extracting, cleaning and maintaining data related to the databases.
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Data Engineers and commands on many programming languages such as Python, R, Java, and C/C++ or database systems SQL, Apache Spark, Hadoop and NoSQL allow them to make raw data very useful. They help make the analysis pipeline smoother and more productive.
After knowing the varied roles and responsibilities the question weaves around that data analyst job salary. But before you understand the salary structure, you need to know the skills needed to be a data analyst as skills are one of the deciding factors in your pay.
Data Analysts must handle ‘big data’ which is a collection of structured (data that is easy to analyze and conforms to a tabular format such as names, addresses or contact information) and unstructured data (data that does not conform to a single format and are stored in formats other than relational databases such as audio files, videos, pictures, etc.). This information overload is driven by a higher degree of volume, variety and speed. For an intensive amount of data, an analyst should be proficient in database systems such as SQL Server, Oracle, Excel and SAP to manage this data.
The interested parties could not understand the complex jargon of the data procured by the data analyst. Therefore, to present a simplified version an analyst needs to visualize and report the data clearly. For this reason, an analyst should have an understanding of visualization tools. For example, Tableau, Business Objects, PowerBI and Jupyter Notebook. The more understanding of these tools the better the data communication will be to investors, customers and stakeholders. For example, to explain the data visually, a data analyst can use pie charts, graphs, presentations, etc.
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Intermediate knowledge of programming languages such as R or Python, Java, PHP, etc. increases your efficiency in solving complex business queries and analyzing data. In addition, a skill like this could be a bonus in a data analyst salary for a fresher. It will make you stand out from the rest.
To arrive at the best possible solution to the given data an analyst must be efficient in creating methodologies and statistical algorithms to work well. To arrive at an object-oriented decision, error-free solution an analyst should be well-versed with mathematical skills, a good understanding of mathematical equations and statistical approaches.
As mentioned above, an analyst can work in different industries from marketing to finance, or operations to sales. To understand the data well, and come up with the best possible solutions, a data analyst should have comprehensive knowledge of the industries. From external factors that affect the work day to internal factors that are small yet have a significant impact on the company must be in the knowledge of a data analyst.
It goes without saying that an analyst should be an expert in analyzing data. A data analyst should be updated on the latest trends, patterns, news for solutions to specific problems. In addition, a basic knowledge of working with analytical tools such as Google Analytics, Adobe Marketing Suite, Google 360 and Google Tag Manager will help in improving your analysis.
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Soft skills also play a role in projecting your work ethic. Therefore, for each different job description, there is a certain set of soft skills that an employer is looking for in an employee. Below are mentioned some of the soft skills required for a data analyst
If you have already completed your degree in data analysis, then you should know that this is just the first step towards success.
It all depends on your willingness to improve your skills. As mentioned above, you can move beyond the field of data analyst to data scientist as well which is a more complex position, but also requires a specific set of skills and a detailed understanding of programming languages, statistical algorithms.
Career scope for a fresher in data analysis could move towards Business Analyst to a greater advancement in Data Science.
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